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Knowledge Extraction and Mining in Biomedical Research Using Rule Network Model

  • Conference paper
Brain and Health Informatics (BHI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8211))

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Abstract

Recent findings show that the quantity of published biomedical literature is increasing at a dramatic rate. Carrying out knowledge extraction from large amounts of research literature becomes a significant challenge. Here we introduce an automatic mechanism for processing such information and extracting meaningful medical knowledge from biomedical literature. Data mining and natural language processing (NLP) are applied in a novel model, called biomedical rule network model. Using this model, information and relationships among herbal materials and diseases, as well as the chemical constituents of herbs can be extracted automatically. Moreover, with the overlapping chemical constituents of herbs, alternative herbal materials can be discovered, and suggestions can be made to replace expensive treatment options with lower cost ones.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Hong Kong Baptist University, Hong Kong

    S. W. Chan & C. H. C. Leung

  2. Department of Mathematics & Computer Science, University of Perugia, Italy

    A. Milani

Authors
  1. S. W. Chan
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  2. C. H. C. Leung
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  3. A. Milani
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Editor information

Editors and Affiliations

  1. Department of Systems Life Engineering, Maebashi Institute of Technology, 460-1 Kamisadori-cho, 371-0816, Maebashi, Gunma, Japan

    Kazayuki Imamura

  2. Electronics-Inspired Interdisciplinary Research Institute, Toyohashi University of Technology, 1-1 Hibarigaoka Tenpaku-cho, 441-8580, Toyohashi, Aichi, Japan

    Shiro Usui

  3. Department of Neurobiology and Behavior, Gunma University Graduate School of Medicine, 39-22 Showamachi 3-chome, 371-8511, Maebashi, Gunma, Japan

    Tomoaki Shirao

  4. The Smith Kettlewell Eye Research Institute, 2318 Fillmore Street, 94115, San Francisco, CA, USA

    Takuji Kasamatsu

  5. University of Rostock, 18051, Rostock, Germany

    Lars Schwabe

  6. Department of Life Science and Informatics, Maebashi Institute of Technology, 460-1 Kamisadori-cho, 371-0816, Maebashi, Gunma, Japan

    Ning Zhong

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© 2013 Springer International Publishing Switzerland

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Chan, S.W., Leung, C.H.C., Milani, A. (2013). Knowledge Extraction and Mining in Biomedical Research Using Rule Network Model. In: Imamura, K., Usui, S., Shirao, T., Kasamatsu, T., Schwabe, L., Zhong, N. (eds) Brain and Health Informatics. BHI 2013. Lecture Notes in Computer Science(), vol 8211. Springer, Cham. https://doi.org/10.1007/978-3-319-02753-1_51

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  • DOI: https://doi.org/10.1007/978-3-319-02753-1_51

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02752-4

  • Online ISBN: 978-3-319-02753-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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